<i>Escherichia coli</i> antimicrobial susceptibility profile and cumulative antibiogram to guide empirical treatment of uncomplicated urinary tract infections in women in the province of Québec, 2010–15
Bibliographic record
Abstract
OBJECTIVES: Empirical treatment of uncomplicated urinary tract infections (UTIs) in women should be based on local susceptibility data. We aimed to generate regional and provincial cumulative antibiograms combining data from different laboratory information systems and determine the impact of basic patient characteristics on susceptibility results. METHODS: All positive urine samples for Escherichia coli obtained from women aged 18-65 years old in outpatient settings between 1 April 2010 and 31 March 2015 from four hospitals in Quebec, Canada, were included. The cumulative antibiogram for ciprofloxacin, nitrofurantoin and trimethoprim/sulfamethoxazole was calculated. A clinically significant difference in susceptibility profile was defined as factor(s) that lowered the susceptibility proportion below 80%. RESULTS: A total of 36 293 positive urine cultures were analysed. In the last year of the study, the proportion of susceptibility for ciprofloxacin, nitrofurantoin and trimethoprim/sulfamethoxazole was 90.3%, 95.4% and 81.9%, respectively. The susceptibility proportion was <80% for trimethoprim/sulfamethoxazole in the Montreal region (73.4%; 95% CI 71.1%-75.9%), whereas it remained >80% for the other regions. A significant decrease in susceptibility with time was identified for ciprofloxacin (92.1%-90.3%, P < 0.001) and nitrofurantoin (97.1%-95.4%, P < 0.001). Increasing age, recent hospitalization and site of collection were associated with an increase in resistance for certain antibiotics. CONCLUSIONS: Overall, all first-line antimicrobials remain acceptable choices for empirical treatment of uncomplicated UTIs in women in Quebec. The regional variability in susceptibility data within a single province emphasizes the importance of local susceptibility data to inform the development of empirical treatment guidelines for UTIs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".